Review: Contextual factors influencing pain response to heelstick procedures in preterm infants: What do we know? A systematic review
Bibliographic record
Abstract
UNLABELLED: Major efforts to develop objective measurement tools for neonatal pain assessment have been made. However, the challenge of measuring pain in neonates remains suggesting that contextual factors (cFs) might alter their responses to pain. Although the role of cFs is increasingly discussed as crucial for pain assessment, they are not well described in the literature and are rarely considered in the clinical setting despite their importance. AIM: To systematically examine studies investigating the impact of cFs on pain response in preterm infants. METHOD: A literature search was undertaken for the period from 1990 to 2009. Studies reporting the relation between one or more cFs and pain response in preterm infants during a heelstick procedure were considered for inclusion. RESULTS: Twenty-three studies satisfied inclusion criteria. The studies varied relative to their design, sample, analysis procedures, and variables examined. Six categories of cFs emerged: age, pain exposure, health status, therapeutic interventions, behavioral status, and demographic factors. The examined cFs varied in the strength of their association with pain response, although none were invariably related, as evidenced by contradictory findings. In some cases the inconsistencies appeared attributable to methodological limitations in studies. Behavioral and physiological pain responses were not always in agreement as would be expected. CONCLUSION: This review supports the influence of some cFs on pain response. However, the results remain inconclusive which may be, in part, related to the heterogeneity of the studies. Contextual factors need further investigation for a better understanding of the magnitude of their effect on pain response.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.056 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.008 |
| Bibliometrics | 0.008 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".